docstr: Computes the ELMo embeddings for a single tokenized sentence.
  
  Please note that ELMo has internal state and will give different results for the same input.
  See the comment under the class definition.
  
  Parameters
  ----------
  sentence : ``List[str]``, required
      A tokenized sentence.
  
  Returns
  -------
  A tensor containing the ELMo vectors.
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code: def embed_sentence(self, sentence):
      """
      Computes the ELMo embeddings for a single tokenized sentence.
  
      Please note that ELMo has internal state and will give different results for the same input.
      See the comment under the class definition.
  
      Parameters
      ----------
      sentence : ``List[str]``, required
          A tokenized sentence.
  
      Returns
      -------
      A tensor containing the ELMo vectors.
      """
  
      return self.embed_batch([sentence])[0]
  
imports: from __future__ import with_statement
  from __future__ import absolute_import
  import argparse
  import json
  import logging
  import os
  import warnings
  import numpy
  import torch
  from allennlp.common.tqdm import Tqdm
  from allennlp.common.util import lazy_groups_of, prepare_global_logging
  from allennlp.common.checks import ConfigurationError
  from allennlp.data.token_indexers.elmo_indexer import ELMoTokenCharactersIndexer
  from allennlp.nn.util import remove_sentence_boundaries
  from allennlp.modules.elmo import _ElmoBiLm, batch_to_ids
  from allennlp.commands.subcommand import Subcommand
label_desc: Use image node_id 3 for calling the ElmoEmbedder obj's underlying member method code with example usage: obj.embed_sentence(sentence) and returns: self